Coupling Of Subsystems Research Articles

Parametric analysis of a fully coupled USV-type wave energy converter: An approach based on wave-to-grid modelling

The integration of the wave energy converter and the unmanned surface vehicle (USV), which has the power generation capability and the mobile capability, is attracting increasing attention in concept design, control, and parametric study, as the integrated system can play a crucial role in the maritime sectors of commerce, science, and military. Enhancing the power generation of a USV-integrated wave energy converter contributes to prolonged USV operations or grid supply, but the power generation performance of this new-type device is significantly influenced by its various coupled subsystems, which requires a systematic methodology for distinguishing key design parameters. To address that problem, a comprehensive wave-to-grid model that reflects all subsystem coupling, energy losses, and constraints is developed to comprehensively describe system dynamics, and then a Taguchi method is employed to investigate the influence of selected design parameters on electric power generation. Results reveal that the piston area of the hydraulic cylinder and the accumulator pressure are the two most influential parameters affecting the time-averaged electric power of the proposed USV-type wave energy converter. The proposed methodology provides guidelines for technicians on how to design wave energy converters optimally.

Reduced-Order Modeling for Dynamic System Identification with Lumped and Distributed Parameters via Receptance Coupling Using Frequency-Based Substructuring (FBS)

Paper presents an effective technique for developing reduced-order models to predict the dynamic responses of systems using the receptance coupling and frequency-based substructuring (RCFBS) method. The proposed approach is particularly suited for reconfigurable dynamic systems across various applications, like cars, robots, mechanical machineries, and aerospace structures. The methodology focuses on determining the overall system receptance matrix by coupling the receptance matrices (FRFs) of individual subsystems in a disassembled configuration. Two case studies, one with distributed parameters and the other with lumped parameters, are used to illustrate the application of this approach. The first case involves coupling three substructures with flexible components under fixed–fixed boundary conditions, while the second case examines the coupling of subsystems characterized by multiple masses, springs, and dampers, with various internal and connection degrees of freedom. The accuracy of the proposed method is validated against a numerical finite element analysis (FEA), direct methods, and a modal analysis. The results demonstrate the reliability of RCFBS in predicting dynamic responses for reconfigurable systems, offering an efficient framework for reduced-order modeling by focusing on critical points of interest without the need to account for detailed modeling with numerous degrees of freedom.

Construction and preliminary application of large language model for reservoir performance analysis

A large language model (LLM) is constructed to address the sophisticated demands of data retrieval and analysis, detailed well profiling, computation of key technical indicators, and the solutions to complex problems in reservoir performance analysis (RPA). The LLM is constructed for RPA scenarios with incremental pre-training, fine-tuning, and functional subsystems coupling. Functional subsystem and efficient coupling methods are proposed based on named entity recognition (NER), tool invocation, and Text-to-SQL construction, all aimed at resolving pivotal challenges in developing the specific application of LLMs for RDA. This study conducted a detailed accuracy test on feature extraction models, tool classification models, data retrieval models and analysis recommendation models. The results indicate that these models have demonstrated good performance in various key aspects of reservoir dynamic analysis. The research takes some injection and production well groups in the PK3 Block of the Daqing Oilfield as an example for testing. Testing results show that our model has significant potential and practical value in assisting reservoir engineers with RDA. The research results provide a powerful support to the application of LLM in reservoir performance analysis.

A BPSO based collaborative management platform for multi-source data security in power grids

By designing a digital power grid multi-source data security collaborative management platform, the system configuration problem of the OMS system and the power grid management platform for the main distribution network of the power grid is solved. A design method for the digital power grid multi-source data security collaborative management platform based on discrete particle swarm optimization algorithm is proposed. Based on the design concept of SOA, realize the overall design framework of the platform according to the design method of multi-layer technical system in the business presentation layer, business process and composition layer, service layer, component layer and resource layer, realize the basic layer design of the system management platform through the basic application platform design scheme of XML configuration, implement the query, processing and output representation of the grid’s multivariate data using B/S architecture protocol, and use the Spring Framework The platform software architecture is implemented using J2EE technology and multi module component design scheme. The discrete particle swarm optimization algorithm is used for the fusion and scheduling of multi-source data in the digital power grid. The interface design and functional construction of the power grid management platform are implemented in the OMS system of the power grid main distribution network, and the logical model of the transformation project is constructed to achieve platform optimization and construction. Tests have shown that the designed digital power grid multi-source data security collaborative management platform has good human-machine interaction, strong data fusion scheduling ability, reduced resource and subsystem coupling, and supports the flexibility of physical deployment and maintenance.

Evaluating water resource carrying capacity in Pearl River-West River economic Belt based on portfolio weights and GRA-TOPSIS-CCDM

Research on the spatial differences in the water resource carrying capacity (WRCC) and their causes can effectively address the imbalance of water resources and enhance the economic, social, and ecological properties of the basin. Sixteen cities in the Pearl River-West River Economic Belt (PR-WR EB) were selected for this study from 2017 to 2021. Based on the theoretical Driving-Pressure-State-Impact-Response model and related research, an evaluation model for WRCC was constructed. The weights obtained from the entropy method and CRITIC method were combined and assigned using the geometric method, after which they were applied to a model that combines the grey relational analysis (GRA), technique for order preference by similarity to ideal solution (TOPSIS), and coupling coordination degree model (CCDM) to calculate the evaluation value of the WRCC subsystem. Meanwhile, the spatial variability and spatial correlation of WRCC were analyzed using the natural breakpoint method, Moran's index, clustering characteristics, and outlier index. The overall WRCC of the PR-WR EB showed stable characteristics from 2017 to 2021. In terms of spatial correlation, significant spatial clustering characteristics were observed. The subsystem coupling degree ranged between 0.6 and 1.0 for all subsystems, thus exhibiting good coupling efficiency; meanwhile, the coordination degree was low and ranged between 0.17 and 0.36.

Study on the coupling and interaction of ecological civilization subsystems in China's Yangtze river economic belt: from the perspective of "production-living-ecological space"

Study on the coupling and interaction of ecological civilization subsystems in China's Yangtze river economic belt: from the perspective of "production-living-ecological space"

IMPLEMENTATION OF A SYSTEMATIC APPROACH TO THE ANALYSIS OF THE STRUCTURE OF ECONOMIC SECURITY OF ENTERPRISES IN THE AGRICULTURAL SECTOR OF UKRAINE

The article is devoted to implementing a systematic approach to developing the economic security structure of enterprises in Ukraine's agrarian sector. It is substantiated that the economic security of enterprises of the agrarian sector of the economy as a system should include the following components: food; environmental safety; biological (resource); financial and credit; social; inventory management and management; social indicators; insurance coverage; state regulation; agricultural cooperation; Monitoring; agricultural information; agriculture and animal husbandry; Machines; employment; Trade; wholesale food markets; scientific support, etc. This creates an idea of the structural and logical scheme of interconnection and mutual influence of the main elements of the system of economic security of agricultural enterprises. It is determined that the elements and subsystems of the system of economic security of enterprises in the agricultural sector are marked by specific principles. In particular, it is determined that the resource principle means that the subsystems interact with resource flows to provide all the necessary resources for the implementation of the main goal – economic security in the agricultural sector; the information principle provides for the exchange of information between subsystems to ensure the stability of the entire system; the organizational principle defines the interconnection of subsystems for the effective achievement of the main goal; technological principle denotes the technological coupling of subsystems in the process of transforming resources to achieve the goals of food and raw material supply; The functional-target principle determines that subsystems with their target functions contribute to the achievement of the overall goal - the economic security of the agricultural sector. A typology of structural components of an agrarian enterprise's management of economic security has been developed. The substantiation of the allocation of functional components and elements of this system is carried out. The typology of structural components of the system of management of economic security of an agricultural enterprise includes such elements as environmental, resource, financial and credit, integration, monitoring, information, production, technical and technological, personnel and sales, as well as a component of scientific and innovative support, inventory management, insurance provision, state regulation.

Assessment of urban resilience and subsystem coupling coordination in the Beijing-Tianjin-Hebei urban agglomeration

Building resilient cities is a novel concept for dealing with risk crises and achieving sustainable urban development in modern times. This paper utilized data from the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) spanning from 2009 to 2019, along with the CRITIC-Entropy weight method, coupling coordination degree (CCD) model and spatial correlation analysis to measure urban resilience and investigate subsystem coupling coordination relationships while considering spatial clustering characteristics. The results indicate that: (1) Spatially, there is a significant gap between the UR index of cities in Hebei Province and that of Beijing-Tianjin, with a “Beijing-Tianjin dual-core driven” trend. Regarding temporal evolution, the growth trend of the UR index is consistent with that of the subsystem resilience index. (2) In general, the CCD of the urban resilience subsystem is slowly trending upwards, with the overall CCD level of BTHUA ranging from primary coordination to moderate coordination. (3) The degree of spatial correlation of subsystem CCD in BTHUA is weak, and more cities exhibit heterogeneous agglomeration. These findings provide valuable inspiration and reference for resilient city construction and coordinated regional development to a certain extent.

MJAR: A novel joint generalization-based diagnosis method for industrial robots with compound faults

Compound faults inevitably occur in multi-joint industrial robots resulting in excessive vibration. Intelligent diagnosis for the occurrence and position of fault joints can efficiently reduce the maintenance cost. Compared with laboratory disassembly parts, joint diagnosis of in-situ industrial robots is more challenging due to coupling of multiple subsystems and the industrial noise interference. This paper proposes a novel joint generalization-based fault diagnosis method for industrial robots via the multi-joint attention residual network (MJAR) model. Each joint signals are independently input to parallel residual convolution with unidirectional matrix kernel (ResCUM) in multi-joint decoupling attention (MJDA) module, which is exclusively designed combining residual and attention mechanism to provide decoupling capability of compound faults. And the multi-spatial reconstruction (MSR) module based on sparse sampling is design to provide multi-scale feature extraction adapted to real industrial signals. MJAR can diagnose unseen compound fault combinations without using any transfer strategy as the robot joint generalization-based fault diagnosis (RJGFD) framework. Integrated experiment results show that the MJAR is superior to some advanced congener DL methods.

Multiferroics in two dimensions: The coupling of mechanical, magnetic and ferroelectric subsystems in van der Waals materials

In this short review the coupling of various subsystems of crystal in van der Waals magnetic materials are considered: the magnetoelectric effect mediated by antisymmetric antiferromagnetic ordering, the ferrovalley-mediated coupling of antiferromagnetism and electric polarization as well as the effects induced by flexural deformations: the spin flexoelectric effect as a curvature induced Dzyaloshinskii-Moriya interaction and flexomagnetic effect as a curvature-induced decompensation of layer magnetization in antiferromagnetic bilayers.

MSRCN: A cross-machine diagnosis method for the CNC spindle motors with compound faults

The cross-machine diagnosis of CNC spindle motors with compound faults is essential and challenging because of the subsystem coupling and individual difference. This paper proposed an in-situ fault diagnosis method for cross machine-level individual diagnosis. Plug-and-play modules are specifically designed inspired by signal processing theory, and are embedded into mainstream CNN-based models as an effective industrial diagnostic model, the multiscale spatial–temporal residual capsule neural networks (MSRCN). The internal mechanism of these new modules is explored through ablation experiments and visualization on real industrial motor signals, which shows MSRCN-based models can enrich the multi-scale feature extraction capabilities and benefits the interference resistance of individual related features. In addition, new evaluation operators for degree of confidence are proposed to comprehensively evaluate the performance of deep learning in classification tasks and the reliability of the decision-making.

Resilience assessment of the nitrogen flow system in food production and consumption for sustainable development on the Qinghai-Tibet Plateau

A robust and resilient nitrogen (N) flow system can effectively ensure consistent food production and consumption activities while preserving environmental quality. In this study, we constructed an indicator system to evaluate N flow system resilience including food production and consumption, at the county scale on the Qinghai-Tibet Plateau (QTP) from 1998 to 2018. The subsystem coupling coordination degree (CCD) and the effect of N losses on N flow system resilience were subsequently explored. The results indicated that despite the overall N flow system resilience remaining low and exhibiting spatiotemporal disparities from 1998 to 2018, over 90 % of the counties experienced improvements. High resilience areas (>0.15) were mainly concentrated in some counties in Sichuan Province, where N losses were positively correlated with system resilience. The level of resilience depended on agricultural and livestock development, and the CCD of subsystems was also high (>0.5) in this region, with the most balanced environmental and socioeconomic development. The low system resilience areas were concentrated in the eastern part of the QTP, where human activities caused substantial disturbances. The fragmentation of the agro-pastoral system coupled with the low system resilience of the food production and driving pressure subsystems led to low CCD between subsystems. In contrast, the western regions, characterized by a stable food production system, high food self-sufficiency, and weak dependence on external systems, showed a higher degree of system resilience and resistance. Our findings provide a reference for N resource management and policy formulation for food production and consumption in the agricultural and pastoral areas of the QTP.

Cavity Jahn-Teller polaritons in molecules

We investigate Jahn-Teller (JT) polaritons, which emerge from the interaction of the two normal-incidence electromagnetic modes with perpendicular polarizations in a Fabry-Perot cavity resonator with JT active systems. These JT polaritons are characterized by a mixed $(+/-)$--circular electromagnetic polarization that originates from the molecular JT vibronic coupling of the material subsystem. Consequently, the exchange of photonic and vibronic angular momenta can be very efficient; exciting the cavity-JT system with short, polarized light pulses results in a dynamical and oscillatory response of the polarization in the cavity medium. Due to the photonic-vibronic coupling, we show how the cavity polarization direction becomes frequency dependent and does not necessarily coincide with the polarization direction of the external fields used to drive the system.

Coupling coordination of new urbanization in Chinese urban agglomeration-characteristics and driving factors.

The coordinated development of new urbanization (NU) in urban agglomerations (UAs) is key for promoting sustainable urban development and the way to achieve Chinese-style modernization. Based on the mechanisms of coupling and coordination of NU, the internal subsystem coupling coordination of NU was deconstructed into five dimensions-economic, population, land, social, and ecological. Using 200 cities in 19 Chinese UAs areas, the spatio-temporal evolution characteristics of the coupling coordination degree of NU (CCDNU) were analyzed, and the driving factors were analyzed from both spatial spillover effect and stratification heterogeneity. The results are as follows: (1) CCDNU has increased from moderate disorder to barely coordinated, exhibiting a spatial distribution of a higher CCDNU in the east and lower CCDNU in the west with a positive global spatial autocorrelation feature; (2) economic drive, population concentration, spatial carrying capacity, and environmental quality play facilitating roles in the CCDNU of the study region, while the spatial carrying capacity, quality of life, and environmental quality inhibit the CCDNU of neighboring regions. From the decomposition of long- and short-term effects, both direct and indirect effects of driving factors were found to accumulate significantly over time. In addition, the model results were robust after replacing the geographic distance weight matrix and excluding the extreme values; (3) the spatial carrying capacity, population concentration, and economic drive are the dominant factors affecting the CCDNU in China. The dominant driving factors of are different in different regions. Meanwhile, the interaction detection shows that the interaction of each driver exhibits a two-factor enhancement or non-linear enhancement. Based on these results, corresponding policies are recommended.

Perturbations in the characteristics of ionospheric HF radio waves during the April 11, 2019, earthquake in Japan: Results from oblique sounding

The Harbin Engineering University HF software-defined radio system since 2018 continuously monitors dynamic processes launched in the ionosphere by energetic events in the Sun–interplanetary-medium–magnetosphere–ionosphere–subsystem coupling. The data collected during the submarine magnitude 6.0 earthquake that occurred off the East coast of Honshu, Japan, on April 11, 2019, have been analyzed with the specific objectives of determining the ionospheric response to the earthquake, the distortions of the radio-wave propagation channels, and identifying possible mechanisms for the transport of the disturbances at 845–2,260 km great-circle distances between the epicenter and the propagation path midpoints. Despite the ionospheric responses to powerful earthquakes have been studied since 1964, the problem of deriving global specifications of the disturbances remains pressing. The effects that the ionospheric disturbances from earthquakes have on radar, communications channels, radio navigation, radio astronomy, etc., are a matter of even greater urgency. The multiple path multifrequency radio system for sounding the ionosphere at oblique incidence provides a convenient tool for diagnosing such HF radio-wave propagation problems, acquiring a database containing the complex amplitudes of the signals and used to produce a sequence of Doppler spectra, for the first time, at a rate of 480 spectra per 1 h along 14 radio-wave propagation paths simultaneously with a 7.5-s temporal resolution and 0.02-Hz Doppler resolution over 20-s intervals. Analysis of the Doppler spectra, Doppler shift along the main ray, and signal amplitudes on the day when the earthquake occurred and on quiet time reference days showed that after the earthquake the Doppler spectra exhibit essential broadening, the Doppler shift along the main ray undergoes alternating sign Doppler variations, as well as quasi-sinusoidal variations with 3–5- and 10–20-min periods pertaining to the infrasound and atmospheric gravity wave frequency bands. The relative amplitudes of disturbances in the electron density are estimated to be ∼1% and 2–19% in the fields of infrasound of atmospheric gravity waves, respectively.

Construction and influencing factors of an early warning system for marine ranching ecological security: Experience from China's coastal areas

Marine ranching has been widely considered as a new mode of marine fishery production. Marine ranching ecological security (MRES) is the basis and premise to ensure the sustainable utilization of marine ranching functions. In this study, an MRES early warning system was constructed based on comprehensive marine ranching ecological security index (CMRESI) and system dynamic model to reveal the main factors affecting the development of marine ranching and explore the changes in MRES under different future development scenarios in China's coastal areas from 2011 to 2035. The results showed that (1) the mean CMRESI of China was only 0.3265 and spatial heterogeneity was significant, showing a general security state; (2) coupling and coordination degree of MRES subsystems was high in Jiangsu, Fujian, Shandong, and Guangdong, and resources was a major constraint on the coordinated development of MRES in the study area (63.6%); (3) Under the ecological priority development scenario, the CMRESI will be the highest in 2035; however, 27% of MRES (in Jiangsu, Fujian, and Hainan) will continue to issue serious early warnings. This study could provide a reference for construction planning, management maintenance, and decision-making of marine ranching.

Features of the Magnetic State of an Ordered Array of Ferromagnetic Ribbons

The features of the magnetic state of an array of parallel oriented permalloy ribbons are discussed. The arrays are made by explosive lithography. The ribbons have a thickness of 180 nm, a width of 2.8 μm, and a length of about 4 mm. The distance between ribbons in different samples varies in the range from 300 nm to 4 μm. It is found that the ribbons in the regions far from the end faces are in a single-domain state with small-angle ripples, the magnetization distribution of which correlates with inhomogeneities of the ribbon side surfaces. Moreover, there is a distinct relationship in the spatial distribution of the ripples between adja-cent ribbons with a relatively small distance between them. This makes it possible to evaluate the role of the magnetostatic coupling of magnetic subsystems of array elements and to estimate the characteristic value of the random stray field that pins the magnetization.

Model decomposition-based fault-tolerant control for interconnected wave partial differential equation systems

The fault-tolerant control (FTC) issue for a class of interconnected wave-distributed parameter systems is addressed by using the inclusion principle. Both subsystem faults and coupling faults are considered. First, the original system is expanded into an equivalent decoupled system. The main structure of the expanded system consists of multiple pair-wise subsystems. Second, the pair-wise fault-tolerant controllers are designed to stabilise the pair-wise subsystems, which can compensate for the effects of subsystem faults and major coupling faults. Third, a coordinated fault-tolerant controller with a suitable coordinated compensator for the expanded system is constructed according to the pair-wise fault-tolerant controllers of all subsystems. The coordinated compensator is used to compensate for the effects of other minor interconnections and coupling faults, and the coordinated controller is designed for the expanded system. Furthermore, the fault-tolerant controller is obtained to guarantee asymptotical stability of the faulty interconnected wave system by satisfying the contraction condition. The numerical experiments are presented to illustrate the effectiveness of the FTC method.

Coupling coordination degree of environment, energy, and economic growth in resource-based provinces of China

Environmental deterioration by natural resources development has emerged as an important concern recently. To address this concern, we constructed a tri-system evaluation index for environment, energy, and the economy and used the entropy value method and the coupling coordination degree model to analyze spatiotemporal changes in the coupling and coordination of subsystems in 10 of China's resource-based regions between 2011 and 2020 and found that the coupling and coordination level of the energy–economy–environment (3E) system in China's resource-based regions is characterized by fluctuating growth with an overall positive developmental trend. The average coupling coordination level increased from 0.541 in 2011 to 0.643 in 2020, reaching the primary coupling coordination stage. Clear heterogeneity exists between various resource-based regions: eastern regions perform better than western, and western better than central. Eastern regions Guangdong, Shandong, and Tianjin achieved coordinated development, while Liaoning exhibits the lowest coupling coordination level. The western regions vary considerably: Shanxi exhibits the highest degree of primary coupling coordination, whereas Qinghai, on the verge of dysfunctional recession, exhibits the lowest. The central regions vary the least; all exhibit minimal coupling coordination. These facts indicate that to enhance the coupling coordination level of China's 3E system in an integrated manner, each region must formulate a differentiated optimization strategy to compensate for its developmental shortcomings.

In-situ fault detection for the spindle motor of CNC machines via multi-stage residual fusion convolution neural networks

The faults from the spindle motor of CNC machines result in excessive vibration affecting the manufacturing quality. In-situ signals of intact motors are complex and nonlinear due to coupling of multiple subsystems. The manufacturing and assembly errors lead to individual differences resulting in more challenging fault detection of motor systems compared with detection of disassembly parts in an experimental environment. In this paper, an in-situ fault diagnosis method via the multi-stage residual fusion convolution neural networks (MSRFCNN) model is proposed. The MSRFCNN with excellent generalization is specially designed for the cross-individual detection of the motor systems, which can extract comprehensive individual-irrelevant features from in-situ multi-channel signals with industrial noise. Integrated experiments are performed on real industrial motor datasets for assessing and analyzing the effectiveness of the proposed method. The experiment results show that the MSRFCNN is superior to classical and some state-of-the-art DL methods.